Model Comparison

Comprehensive side-by-side analysis of model capabilities and performance

Meta

Llama 3.2 3B Instruct

Meta

Llama 3.2 3B Instruct is a language model developed by Meta. The model shows competitive results across 15 benchmarks. It excels particularly in NIH/Multi-needle (84.7%), ARC-C (78.6%), GSM8k (77.7%). It supports a 256K token context window for handling large documents. The model is available through 1 API provider. Released in 2024, it represents Meta's latest advancement in AI technology.

Microsoft

Phi-3.5-vision-instruct

Microsoft

Phi-3.5-vision-instruct is a multimodal language model developed by Microsoft. It achieves strong performance with an average score of 68.3% across 9 benchmarks. It excels particularly in ScienceQA (91.3%), POPE (86.1%), MMBench (81.9%). The model shows particular specialization in general tasks with an average performance of 75.9%. As a multimodal model, it can process and understand text, images, and other input formats seamlessly. It's licensed for commercial use, making it suitable for enterprise applications. Released in 2024, it represents Microsoft's latest advancement in AI technology.

Microsoft

Phi-3.5-vision-instruct

Microsoft

2024-08-23

Meta

Llama 3.2 3B Instruct

Meta

2024-09-25

1 month newer

Performance Metrics

Context window and performance specifications

Meta

Llama 3.2 3B Instruct

Larger context
Max Context:256.0K
Parameters:3.2B
Microsoft

Phi-3.5-vision-instruct

Max Context:-
Parameters:4.2B

Performance comparison across key benchmark categories

Meta

Llama 3.2 3B Instruct

general
42.5%
math
+17.4%
61.3%
Microsoft

Phi-3.5-vision-instruct

general
+33.5%
75.9%
math
43.9%

Provider Availability & Performance

Available providers and their performance metrics

Meta

Llama 3.2 3B Instruct

1 providers

DeepInfra

Throughput: 171.5 tok/s
Latency: 0.24ms
Microsoft

Phi-3.5-vision-instruct

0 providers
Meta

Llama 3.2 3B Instruct

Avg Score:0.0%
Providers:1
Microsoft

Phi-3.5-vision-instruct

Avg Score:0.0%
Providers:0